Text here
This report investigates the impacts of vaccinations amongst the different development regions as we dived into the difference of life expectancy and the global coverage of the vaccination programs. We used a dataset from OWID (Our World In Data) for vaccination coverage and global life expectancy. We analysed the trend of the vaccination programs in different regions to deduce the impact of the vaccines and potential life expectancy gains.
Life Expectancy Data
Life Expectancy dataset from Our World in Data.
Code
le_df <- read_csv("data/life-expectancy.csv")
paged_table(le_df)Cleaning life expectancy data
Code
le_clean <- janitor::clean_names(le_df)
# rename column
le_clean <- le_clean %>%
rename(period_life_expect = period_life_expectancy_at_birth_sex_all_age_0)
paged_table(le_clean)Global Vaccination Coverage Data
Code
vaccination_df <- read_csv("data/global-vaccination-coverage.csv")
vaccination_df %>% paged_table()Cleaning vaccination data
Code
vaccination_clean <- janitor::clean_names(vaccination_df) %>% paged_table()
vaccination_cleanUsing a combination of Pearson’s correlation coefficient and linear regression, the vaccines for one dose of Salk’s polio vaccine, one dose of the meningococcal vaccine, three doses of the polio vaccine and three doses of the DPT (diphtheria, pertussis, tetanus) vaccine were found to be the most significant in increasing life expectancy globally.